Instructions
Team Name: The Fantastic Four
Team Members:
Dataset Description:
(max. 75 words)
Historical Data of various causes of deaths across different countries along the timeline from 1990 up until 2019, Combined with The Population by country to derive more insight into the data
Instructions:
import pandas as pd
import utils
df = pd.read_csv('../data/cause_of_deaths_cont_pop.csv')
# Hypothesis 1 (World Map):
utils.plot_hyp_1_1(df)
# Hypothesis 1 (Matrix):
utils.plot_hyp_1_2(df)
# Hypothesis 2 (World Map):
utils.plot_hyp_2_1(df)
# Hypothesis 2 (World Map):
utils.plot_hyp_2_2(df)
Interpretation:
Based on the Correlation matrix plot we can deduce a moderate positive correlation between the 2 variables with a value of 0.58, the relationship was furtherly explained and reinforced by the second plot of the correlation coeffecient between the 2 variables for each country over the span of 30 years from 1990 to 2019, with the highest Positive Correlation in the US and the highest Negative Correlation in Austria.
Interpretation:
Comparing the Absolute Values and The Relative Values, over the total Population, of the Fatalities due to Road Injuries showed that while the Overall Number of deaths seems to be increasing, the percentage of it to the population is evidently decreasing for different continents, mainly Africa, Asia and Europe, while staying stalled in the rest; which was reflected in the second graph of the average growth rate per country over the span of 30 years from 1990 to 2019.